code: def __call__(
      self, examples: list[Example], task_type: TaskType
  ) -> dict[str, Union[Sequence[float], Sequence[int]]]:
      # TODO: remove this restriction
      if len(examples) > 1:
          raise ValueError(
              f"Batch size of {len(examples)} not currently supported for HF models: please use 1"
          )
      with torch.no_grad():
          if task_type.startswith("classification"):
              classification_examples = cast(
                  "list[ClassificationExample]", examples
              )
              rv = self._evaluate_classification(
                  classification_examples, task_type=task_type
              )
          elif task_type == "numeric":
              numeric_examples = cast("list[NumericExample]", examples)
              rv = self._evaluate_numeric(numeric_examples)
          elif task_type == "sequence_prob":
              sequence_prob_examples = cast(
                  "list[SequenceProbExample]", examples
              )
              rv = self._evaluate_sequence_prob(sequence_prob_examples)
          elif task_type == "logodds":
              logodds_examples = cast("list[LogoddsExample]", examples)
              rv = self._evaluate_logodds(
                  logodds_examples, take_absolute_value=False
              )
          elif task_type == "absolute_logodds":
              logodds_examples = cast("list[LogoddsExample]", examples)
              rv = self._evaluate_logodds(
                  logodds_examples, take_absolute_value=True
              )
          else:
              raise ValueError(f"Unrecognised task type {task_type}")
          return rv
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Union, cast, Sequence
  from typing_extensions import Literal, get_args
  import numpy
  import torch
  import torch.nn.functional
  from transformers import AutoModelForCausalLM, AutoTokenizer
  from accelerate import Accelerator
  from .isp_dataset import ClassificationExample, Example, ExampleWithClasses, LogoddsExample, SequenceProbExample, NumericExample, TaskType
  from .isp_utils import BasicParser
  from .isp_utils import OpenAIModel, OpenaAIModelList
label_desc: Use image node_id 3 for calling the HFModel obj's underlying member method code with example usage: obj.__call__(examples, task_type) and returns: rv